A multi-market scheduling model for a technical virtual power plant coalition

Abstract

During the transitional period of electricity market reforms in China, scheduling simulations of technical virtual power plants (TVPPs) are crucial owing to the lack of operational experience. This study proposes a model for TVPPs participating in the current multi-market; that is, TVPP coordinate bidding in the day-ahead energy and ramping ancillary market while purchasing unbalanced power and providing frequency regulation service in the real-time market. A multi-scenario optimization approach was employed in the day-ahead stage to manage uncertainty, and an improved Shapley value was utilized for revenue allocation. By employing linearization techniques, the model is transformed into a mixed-integer second-order cone-programming problem that can be efficiently solved using linear solvers. Numerical simulations based on actual provincial electricity market rules were conducted to validate the effectiveness of a TVPP coalition profitability.